Background:Dengue is one of the most rapidly spreading vector-borne diseases,which is considered to be a major health concern in tropical and sub-tropical countries.It is strongly believed that the spread and abundanc...Background:Dengue is one of the most rapidly spreading vector-borne diseases,which is considered to be a major health concern in tropical and sub-tropical countries.It is strongly believed that the spread and abundance of vectors are related to climate.Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence.Methods:A host-vector model is constructed to simulate the dynamic of transmission.The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data.Further,the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag(ARDL)model.Results:The infection parameter can be extended when updated daily climates are known,and it can be useful to forecast dengue incidence.This approach provides proper prediction,even when tested in increasing or decreasing prediction windows.In addition,associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengueprecipitation.The range of optimal temperature for infection is 24.3e30.5C.Humidity and precipitation are positively associated with dengue upper the threshold 70%at lag 38 days and below 50 mm at lag 50 days,respectively.Conclusion:Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden.展开更多
Dengue virus infection is a leading health problem in many endemic countries,including Indonesia,characterized by high morbidity and wide spread.It is known that the risk factors that influence the transmission intens...Dengue virus infection is a leading health problem in many endemic countries,including Indonesia,characterized by high morbidity and wide spread.It is known that the risk factors that influence the transmission intensity vary among different age groups,which can have implications for dengue control strategies.A time-dependent four−age structure model of dengue transmission was constructed in this study.A vaccination scenario as control strategy was also applied to one of the age groups.Daily incidence data of dengue cases from Santo Borromeus Hospital,Bandung,Indonesia,from 2014 to 2016 was used to estimate the infection rate.We used two indicators to identify the changes in dengue transmission intensity for this period in each age group:the annual force of infection(FoI)and the effective reproduction ratio based on a time-dependent transmission rate.The results showed that the yearly FoI of children(age 0–4 years)increased significantly from 2014 to 2015,at 10.08%.Overall,the highest FoI before and after vaccination occurred in youngsters(age 5–14 years),with a FoI of about 6%per year.In addition,based on the daily effective reproduction ratio,it was found that vaccination of youngsters could reduce the number of dengue cases in Bandung city faster than vaccination of children.展开更多
基金This work was partially supported by the Indonesian Ministry of Research and Technology(Ristekdikti)or National Agency for Research and Innovation Grant 2020The second author was supported by the Indonesian Ministry of Education and Culture(Kemendikbud)through BU programThe third author was partially supported by the PMDSU grant no.1511/E4.4/2015.
文摘Background:Dengue is one of the most rapidly spreading vector-borne diseases,which is considered to be a major health concern in tropical and sub-tropical countries.It is strongly believed that the spread and abundance of vectors are related to climate.Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence.Methods:A host-vector model is constructed to simulate the dynamic of transmission.The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data.Further,the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag(ARDL)model.Results:The infection parameter can be extended when updated daily climates are known,and it can be useful to forecast dengue incidence.This approach provides proper prediction,even when tested in increasing or decreasing prediction windows.In addition,associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengueprecipitation.The range of optimal temperature for infection is 24.3e30.5C.Humidity and precipitation are positively associated with dengue upper the threshold 70%at lag 38 days and below 50 mm at lag 50 days,respectively.Conclusion:Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden.
基金Part of the research is funded by the Indonesian PDUPT RistekBrin 2021(No:120M/IT1.C02/TA.00/2021)the Indonesian Penelitian Disertasi Doktor RistekBrin 2021(No:120J/IT1.C02/TA.00/2021).
文摘Dengue virus infection is a leading health problem in many endemic countries,including Indonesia,characterized by high morbidity and wide spread.It is known that the risk factors that influence the transmission intensity vary among different age groups,which can have implications for dengue control strategies.A time-dependent four−age structure model of dengue transmission was constructed in this study.A vaccination scenario as control strategy was also applied to one of the age groups.Daily incidence data of dengue cases from Santo Borromeus Hospital,Bandung,Indonesia,from 2014 to 2016 was used to estimate the infection rate.We used two indicators to identify the changes in dengue transmission intensity for this period in each age group:the annual force of infection(FoI)and the effective reproduction ratio based on a time-dependent transmission rate.The results showed that the yearly FoI of children(age 0–4 years)increased significantly from 2014 to 2015,at 10.08%.Overall,the highest FoI before and after vaccination occurred in youngsters(age 5–14 years),with a FoI of about 6%per year.In addition,based on the daily effective reproduction ratio,it was found that vaccination of youngsters could reduce the number of dengue cases in Bandung city faster than vaccination of children.
